온라인 리뷰 데이터 기반의 조직몰입도 측정 체계 구축에 대한 연구A New Organizational Commitment Measurement System Based on Online Review Data

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People want to work for companies with good organizational cultures. Organizational culture is the overall atmosphere of a company, including the ways employees work and the company's operational policy. Organizational culture is the result of transferring core values containing the CEO's beliefs and management philosophy to employees. It is an intangible competitive edge that can differentiate the company from its competitors. In addition, the higher the engagement of employees in strong organizational culture, the better the management performance. Therefore, CEOs want high organizational engagement of employees and want to manage the level of engagement of employees. However, the definition of organizational engagement and the criteria to measure it differs across measuring agencies. This makes it almost impossible to compare the organizational engagement levels among peer companies and difficult to manage or improve them. Furthermore, employee surveys, the most widely used current way to measure the organizational engagement level, have some structural limitations, including the risk of potential distortion and biased answers. To address this problem, we propose a new organizational engagement measurement system using machine learning techniques on online review data about corporates. Using a large amount of data collected from a global corporate review online site, where employees voluntarily and anonymously make posts about their companies, we show that our proposed model is effective compared to the traditional survey-based methods. This new approach to measuring the organizational engagement level does not only enable employees to constantly understand their perception of the company and explain essential phenomena, but also complements the high-cost survey-based diagnostic methods.
Publisher
한국경영과학회
Issue Date
2023-02
Language
Korean
Citation

한국경영과학회지, v.48, no.1, pp.11 - 28

ISSN
1225-1119
URI
http://hdl.handle.net/10203/305599
Appears in Collection
MT-Journal Papers(저널논문)
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